DATA ENGINEER

Overview

Remote
Depends on Experience
Full Time
No Travel Required

Skills

Amazon Redshift
Amazon Web Services
Analytics
Apache Flink
Apache Hadoop
Apache Kafka
Apache Spark
Big Data
Cloud Computing
Collaboration
Communication
Conflict Resolution
Continuous Delivery
Continuous Integration
Data Architecture
Data Engineering
Data Governance
Data Modeling
Data Warehouse
Databricks
Debugging
DevOps
Docker
ELT
Extract
Transform
Load
Good Clinical Practice
Google Cloud Platform
HIPAA
IT Strategy
Kubernetes
Leadership
Machine Learning (ML)
Machine Learning Operations (ML Ops)
Management
Mentorship
Microsoft Azure
Open Source
Optimization
Orchestration
Performance Tuning
Problem Solving
Python
Real-time
Regulatory Compliance
Roadmaps
SQL
Scala
Snow Flake Schema
Streaming
Testing
Use Cases
Workflow

Job Details

Senior Data Engineer (Remote 10+ Years Experience)

About the Role

We are seeking a highly skilled and experienced Senior Data Engineer with 10+ years of expertise in designing, building, and optimizing scalable data platforms. This is a fully remote position, offering the opportunity to work with distributed teams across global time zones. The ideal candidate has deep technical expertise in modern data engineering practices, cloud technologies, and big data ecosystems, with strong problem-solving and leadership abilities.

Responsibilities

  • Architect, design, and implement large-scale data pipelines for batch and streaming use cases.

  • Develop, optimize, and maintain ETL/ELT workflows to ensure efficient data ingestion and transformation.

  • Build and manage data lakes, warehouses, and real-time data platforms (e.g., Snowflake, Databricks, BigQuery, Redshift).

  • Collaborate with data scientists, analysts, and product teams to deliver reliable and high-quality datasets.

  • Ensure data governance, security, and compliance across the data ecosystem.

  • Mentor and guide junior engineers, providing best practices in coding, testing, and architecture.

  • Drive performance tuning and cost optimization of cloud-based data platforms.

  • Participate in technical strategy discussions and contribute to roadmap planning.

Requirements

  • 10+ years of professional experience in data engineering or related roles.

  • Strong expertise in SQL, Python, and/or Scala for data engineering.

  • Hands-on experience with cloud platforms (AWS, Google Cloud Platform, or Azure).

  • Solid background in big data technologies such as Spark, Kafka, Hadoop, or Flink.

  • Proven experience with modern data warehouses (Snowflake, Redshift, BigQuery, Databricks).

  • Strong understanding of data modeling, data architecture, and schema design.

  • Experience with orchestration tools (Airflow, dbt, Prefect, Dagster).

  • Familiarity with CI/CD, containerization (Docker, Kubernetes), and DevOps practices.

  • Strong problem-solving, debugging, and performance-tuning skills.

  • Excellent communication skills and ability to work effectively in remote, distributed teams.

Preferred Qualifications

  • Experience leading data engineering teams or large-scale projects.

  • Background in machine learning pipelines, MLOps, or real-time analytics.

  • Knowledge of data governance frameworks (GDPR, HIPAA, CCPA).

  • Contributions to open-source data engineering tools.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.